An organ or system that has experienced modification is called an illness. People nowadays suffer from a wide range of ailments. It is possible for someone who is not infected to contract the infection and become ill from interacting with an infected person. To mitigate all those issues, we had proposed a machine learning approach. Our primary objective in this project is to lessen the patient’s illness by using the appropriate medications that the doctor has prescribed. These days, machine learning techniques play a major role in medical diagnosis and drug prediction. These technologies help physicians diagnose conditions more quickly, accurately assess patient symptoms, and suggest the best courses of treatment. This advancement has the potential to revolutionize the accuracy of diagnosis and make customized, highly effective treatment plans possible. The project’s objective is to develop a machine learning model that correctly diagnoses medical conditions by integrating reported symptoms and patient demographics. The Naive Bayes algorithm is employed in this project.


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    Titel :

    MEDICARE: Healthcare Prediction Using Machine Learning


    Weitere Titelangaben:

    Smart Innovation, Systems and Technologies


    Beteiligte:
    Jha, Pradeep Kumar (Herausgeber:in) / Jamwal, Prashant (Herausgeber:in) / Tripathi, Brajesh (Herausgeber:in) / Garg, Deepak (Herausgeber:in) / Sharma, Harish (Herausgeber:in) / Tagore, C. H. (Autor:in) / Pooja, H. M. (Autor:in) / Chandan, B. S. (Autor:in) / Srujan, K. (Autor:in) / Beheti, Komal (Autor:in)

    Kongress:

    Congress on Control, Robotics, and Mechatronics ; 2024 ; Warangal, India February 03, 2024 - February 04, 2024



    Erscheinungsdatum :

    31.10.2024


    Format / Umfang :

    11 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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